基于决策到决策路径的遗传算法软件测试用例设计

Design of Software Test Cases of Genetic Algorithm Based on DD-Path

测试用例生成优劣是软件测试自动化效率高低至关重要的一点,常用的随机测试用例自动生成方法虽然实现简单,但具有效率低、冗余大的缺点,而遗传算法适合于处理传统方法难以解决的非线性问题。为了提高测试效率、降低测试成本,通过分析测试用例自动生成和遗传算法的基本理论,在面向决策到决策路径的软件测试基础上,利用程序控制流图详细阐释了对基于遗传算法的测试用例自动生成技术的设计。通过与随机法自动用例生成进行试验对比,表明其效率至少是随机法10倍。

Test cases Generation is one of the crucial points which determine the efficiency of the automated software test. The normal random test cases generation means is easy, but there are inefficient and with great redundant. The GA is fit for solving nonlinear problems which are hard to complete by traditional methods. To overcome the low-efficiency shortcoming of the random test cases generation way, we describe the automatic generation of test cases and the basic theory of Genetic Algorithm （GA）. By using the control flow path table based on DD-path testing, we expatiate the design of automatic generating test cases based on Genetic Algorithm. By the comparison with random test case generation way, it shows that the efficiency of GA test case generation which is at least 10 times than the random way.